Described herein are techniques for estimating the position and orientation of a light-detecting mobile communications device (e.g., cellular telephone, tablet computer, wearable computing device, electronically enhanced eyeglasses) by identifying light beacons in the vicinity of the mobile device and by compensating at least in part for motion of the mobile device, the presence of visual noise, and local irregularities in the Earth's magnetic field.
Indoor positioning services relate to methods in which networks of devices and algorithms are used to locate mobile devices within buildings. Indoor positioning is regarded as a key component of location-aware mobile computing and is a critical element in providing augmented reality (AR) services. Location-aware computing relates to applications that utilize a mobile device user's location to provide content relevant to that location. Additionally, AR is a technology that overlays a virtual space onto a real (physical) space. To successfully enable AR and location-aware computing, accurate indoor positioning is a key requirement. Moreover, indoor positioning and AR services may include displaying on a user's mobile device in real time a spatial map which includes “you are here” information; such information not only should be accurate enough to assist user navigation (e.g., in a retail space) but should be presented in a manner that is clear and agreeable to the user.
Signals from Global Positioning System (GPS) satellites lose significant power when passing through construction materials, and suffer from multi-path propagation effects that make GPS unsuitable for indoor environments. Techniques based on received signal strength indication (RSSI) from WiFi and Bluetooth wireless access points have also been explored for indoor positioning. However, complex indoor environments cause radio waves to propagate in dynamic and unpredictable ways, limiting the accuracy of positioning systems based on RSSI. Ultrasonic techniques, which transmit acoustic waves to microphones, can also be used to approximate indoor position. However, ultrasonic sound waves operate at lower frequencies than systems based on WiFi and attenuate significantly when passing through walls. This attenuation, which limits the spatial reach of waves from an ultrasound source, potentially makes ultrasonic techniques more accurate than WiFi or Bluetooth techniques.
Optical indoor positioning techniques use optical signals, either visible or infrared, and can be used to accurately locate mobile devices indoors. These are more accurate than the approaches mentioned previously, since optical signals are highly directional and cannot penetrate solid objects. However, several limitations, drawbacks, or potential sources of error in optical indoor positioning techniques may need to be addressed.
These include, firstly, a need to reduce noise in the signal derived by a mobile device from images or ambient light levels. Any scheme to detect a signal mixed with noise is made more reliable by reduction of the noise. In particular, an illustrative light-source detection scheme described herein, according to various embodiments of the invention, depends on the detection of spectral peaks (i.e., peaks in the frequency domain) that correspond to identification signals emitted by light sources. The spectrum of a digital image (or other data obtained by sensing light, whether using an image-forming camera, a non-image-forming sensor, or both) is estimated by calculating a Fast Fourier Transform (FFT) of the image or a signal derived by averaging from the data. Each light source emits light having an at least locally unique spectrum whose distinct features (e.g., peaks) constitute the identification code (ID) of that light. ID detection depends on the identification of patterns of peaks that may be obscured or rendered ambiguous by noise in the signal. In essence, signal-to-noise ratio must exceed some threshold for detection to be possible.
A second limitation of indoor positioning that may be addressed is the presentation of location information in a user-friendly way. In a beacon-based positioning system that may show a user of a mobile device their approximate position and orientation on a map displayed on the mobile device, sudden movement of the user's position indicator from one point to another (e.g., from one beacon location to another beacon location, or to the centroid of two or more beacon locations) tends to be disconcerting or irksome to the user. It is therefore desirable to form an estimate of a user's position that moves smoothly, or nearly so, between points on a map.
Thirdly, it is desirable that usefully accurate orientation information be delivered to users of an indoor position system, including the bearers of mobile devices who may be viewing maps of their spatial context on their device displays. Many mobile devices contain a compass or magnetometer that provides heading or orientation information by sensing the Earth's magnetic field. However, in portions of many indoor spaces, the Earth's magnetic field may, in effect, be locally distorted by the proximity of masses of metal or devices that generate magnetic fields. In such areas, raw device measurements of orientation may be misleading. It is therefore desirable to assure that a user's map is accurately oriented.